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Looped Diffusion Transformer reportedly reuses blocks within each denoising step
A post describing the method says deeper loops can outperform adding more denoising steps.
TLDR
A post about Looped Diffusion Transformer says it reuses the same Transformer blocks to iteratively refine hidden states within each denoising step. It says deep supervision and self-modulating attention improve generation without increasing the parameter count, and that scaling loop depth can outperform adding more denoising steps.
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1 Source, first seen ago